Assessment of different head tilt angles in volumetric modulated arc therapy for hippocampus-avoidance whole-brain radiotherapy.

Purpose: In the field of radiation therapy for brain metastases, whole-brain hippocampus-avoidance treatment is commonly employed. this study aims to examine the impact of different head tilt angles on the dose distribution in the whole-brain target area and organs at risk. It also aims to determine the head tilt angle to achieve optimal radiation therapy outcomes. Methods: CT images were collected from 8 brain metastases patients at 5 different groups of head tilt angle. The treatment plans were designed using the volumetric modulated arc therapy (VMAT) technique. The 5 groups of tilt angle were as follows: [0°,10°), [10°,20°), [20°,30°), [30°,40°), and [40°,45°]. The analysis involved assessing parameters such as the uniformity index, conformity index, average dose delivered to the target, dose coverage of the target, hot spots within the target area, maximum dose, and average dose received by organs at risk. Additionally, the study evaluated the correlation between hippocampal dose and other factors, and established linear regression models. Results: Significant differences in dosimetric results were observed between the [40°,45°] and [0°,10°) head tilt angles. The [40°,45°] angle showed significant differences compared to the [0°,10°) angle in the average dose in the target area (31.49 ± 0.29 Gy vs. 31.99 ± 0.29 Gy, p=0.016), dose uniformity (1.20 ± 0.03 vs. 1.24 ± 0.03, p=0.016), hotspots in the target area (33.64 ± 0.35 Gy vs. 34.42 ± 0.49 Gy, p=0.016), maximum hippocampal dose (10.73 ± 0.36 Gy vs. 11.66 ± 0.59 Gy, p=0.008), maximum dose in the lens (2.82 ± 1.10 Gy vs. 4.99 ± 0.16 Gy, p=0.016), and average dose in the lens (1.93 ± 0.29 Gy vs. 4.22 ± 0.26 Gy, p=0.008). There is a moderate correlation between the maximum dose in the hippocampi and the PTV length (r=0.49, p=0.001). Likewise, the mean dose in the hippocampi is significantly correlated with the hippocampi length (r=0.34, p=0.04). Conclusion: The VMAT plan with a head tilt angle of [40°,45°] met all dose constraints and demonstrated improved uniformity of the target area while reducing the dose to organs at risk. Furthermore, the linear regression models suggest that increasing the head tilt angle within the current range of [0°,45°] is likely to lead to a decrease in the average hippocampal dose.

Investigation on the mechanism of androsta-4,6,8,14-tetraene-3,11,16-trione against acute lymphoblastic leukemia.

Steroids are potential anti-leukemia agents, and Epigynum auritum is a Yunnan folk medicine with high levels of androsterone, pregnane, and steroid derivatives. However, the underlying therapeutic mechanism of androsta-4,6,8,14-tetraene-3,11,16-trione (ATT), an androsterone isolated from Epigynum auritum, is not yet clear. This study aimed to explore the anti-leukemia mechanism of ATT using molecular biology, network pharmacology, and molecular docking technology. The cell viability results showed that ATT had an anti-proliferation effect in acute lymphoblastic leukemia cells (CEM/C1, MOLT-4, Jurkat, BALL-1, Nalm-6, and RS4;11). Further studies showed that ATT reduced the mitochondrial membrane potential in B-cell acute lymphoblastic leukemia cell lines (BALL-1, Nalm-6, and RS4;11) and induced cell cycle arrest in MOLT-4 and BALL-1. ATT induced BALL-1 cell apoptosis by activating Caspase 3/7 activity and causing DNA fragmentation. Network pharmacology results suggested that ATT exerts its anti-leukemia activity via the PI3K/Akt signaling pathway. In addition, molecular docking analysis showed that ATT had high scores in docking with PTGS2, NR3C1, and AR. Western blotting results showed that ATT reduced the relative protein level of P-PI3K and P-Akt, thereby increasing the relative level of pro-apoptosis protein Bax and reducing the relative level of anti-apoptosis protein Bcl-2, the apoptosis downstream protein pro-caspase3, and cell proliferation-related proteins (P-GSK3B and CyclinD1). In conclusion, these results demonstrated that ATT could be a potential candidate drug with apoptosis-induction and cell cycle arrest effects for further investigation in acute lymphoblastic leukemia therapy.

Pan-cancer analysis implicates novel insights of lactate metabolism into immunotherapy response prediction and survival prognostication.

BACKGROUND: Immunotherapy has emerged as a potent clinical approach for cancer treatment, but only subsets of cancer patients can benefit from it. Targeting lactate metabolism (LM) in tumor cells as a method to potentiate anti-tumor immune responses represents a promising therapeutic strategy. METHODS: Public single-cell RNA-Seq (scRNA-seq) cohorts collected from patients who received immunotherapy were systematically gathered and scrutinized to delineate the association between LM and the immunotherapy response. A novel LM-related signature (LM.SIG) was formulated through an extensive examination of 40 pan-cancer scRNA-seq cohorts. Then, multiple machine learning (ML) algorithms were employed to validate the capacity of LM.SIG for immunotherapy response prediction and survival prognostication based on 8 immunotherapy transcriptomic cohorts and 30 The Cancer Genome Atlas (TCGA) pan-cancer datasets. Moreover, potential targets for immunotherapy were identified based on 17 CRISPR datasets and validated via in vivo and in vitro experiments. RESULTS: The assessment of LM was confirmed to possess a substantial relationship with immunotherapy resistance in 2 immunotherapy scRNA-seq cohorts. Based on large-scale pan-cancer data, there exists a notably adverse correlation between LM.SIG and anti-tumor immunity as well as imbalance infiltration of immune cells, whereas a positive association was observed between LM.SIG and pro-tumorigenic signaling. Utilizing this signature, the ML model predicted immunotherapy response and prognosis with an AUC of 0.73/0.80 in validation sets and 0.70/0.87 in testing sets respectively. Notably, LM.SIG exhibited superior predictive performance across various cancers compared to published signatures. Subsequently, CRISPR screening identified LDHA as a pan-cancer biomarker for estimating immunotherapy response and survival probability which was further validated using immunohistochemistry (IHC) and spatial transcriptomics (ST) datasets. Furthermore, experiments demonstrated that LDHA deficiency in pancreatic cancer elevated the CD8+ T cell antitumor immunity and improved macrophage antitumoral polarization, which in turn enhanced the efficacy of immunotherapy. CONCLUSIONS: We unveiled the tight correlation between LM and resistance to immunotherapy and further established the pan-cancer LM.SIG, holds the potential to emerge as a competitive instrument for the selection of patients suitable for immunotherapy.

IGF2BP2-related modification patterns in pancreatic cancer: A machine learning-driven approach towards personalized treatment.

Pancreatic cancer (PC) is a malignant digestive system tumor with a very poor prognosis. N6-methyladenosine (m6A) is mediated by a variety of readers and participates in important regulatory roles in PC. Based on TCGA_PAAD, ICGC_AU_PAAD, ICGC_CA_PAAD, GSE28735 and GSE62452 datasets, We mapped the multi-omics changes of m6A readers in PC and found that m6A readers, especially IGF2BP family genes, had specific changes and were significantly associated with poor prognosis. An unsupervised consensus clustering algorithm was used to explore the correlation between specific expression patterns of m6A readers in PC and enrichment pathways, tumor immunity and clinical molecular subtypes. Then, the principal component analysis (PCA) algorithm was used to quantify specific expression patterns and screen core genes. Machine learning algorithms such as Bootstrapping and RSF were used to quantify the expression patterns of core genes and construct a prognostic scoring model for PC patients. What's more, pharmacogenomic databases were used to screen sensitive drug targets and small molecule compounds for high-risk PC patients in an all-around and multi-angle way. Our study has not only provided new insights into personalized prognostication approaches, but also thrown light on integrating tailored risk stratification with precision therapy based on IGF2BP2-mediated m6A modification patterns.

Clinical outcomes of endodontic microsurgery in complicated cases with large or through-and-through lesions: a retrospective longitudinal study.

OBJECTIVES: To investigate the clinical outcomes of endodontic microsurgery in complicated cases presenting with large or through-and-through lesions. MATERIALS AND METHODS: We retrospectively collected and analyzed preoperative, intraoperative, and follow-up data from 143 complicated cases that underwent endodontic microsurgery. Clinical outcomes were assessed in terms of tooth survival and surgery success. Cox regression analysis was used to evaluate the survival rate and identify associated risk factors. Additionally, the success rate was compared across different postoperative periods, and potential factors contributing to surgical failure were identified through binary logistic regression. RESULTS: The overall survival and success rates were 93.0% and 91.7%, respectively. The Cox regression model identified four risk factors affecting tooth survival, including apicoectomy of four teeth (HR = 35.488; P = 0.0002), an open apex observed on preoperative radiographs (HR = 6.300; P = 0.025), the performance of guided tissue regeneration technique (HR = 8.846; P = 0.028), and a palatal surgical approach (HR = 8.685; P = 0.030). The success rate demonstrated an initial increase in the early postoperative period (from 0.5 to 2 years; P = 5.8124e-30), followed by stabilization (from 2 to 9 years; P = 0.298). Surgery success rate significantly declined when apicoectomy involved four teeth (OR = 109.412; P = 0.002). CONCLUSIONS: Endodontic microsurgery demonstrates satisfactory outcomes in complicated cases, maintaining a stable success rate after two years. However, tooth survival and surgery success are significantly compromised when apicoectomy involves four teeth. Factors such as guided tissue regeneration, an open apex, and the palatal surgical approach are associated with an increased risk of tooth extraction. CLINICAL RELEVANCE: Despite achieving acceptable outcomes in complicated cases, endodontic microsurgery is adversely affected by the apicoectomy of four teeth.

Comparative pharmacokinetic analysis of sporoderm-broken and sporoderm-removed Ganoderma lucidum spore in rat by using a sensitive plasma UPLC-QqQ-MS method.

Previous studies have found that removing the sporoderm significantly enhanced antitumor and immunoregulatory activities of Ganoderma lucidum spore (GLS) compared with breaking the sporoderm. However, the pharmacokinetics of sporoderm-removed GLS (RGLS) and sporoderm-broken GLS (BGLS) remain elusive. To compare the pharmacokinetic differences between the two products, we developed a UPLC-QqQ MS method for determining nine representative triterpenoid concentrations. Chloramphenicol was used as an internal standard. The samples were separated on a reversed-phase column using acetonitrile-0.1% formic acid and water-0.1% formic acid as mobile phases. Nine triterpenoids were analyzed using multiple reaction monitoring mode. The results showed that the area under the concentration-time curve from dosing to time t of all nine components was increased in RGLS compared with BGLS. And the time to the maximum concentration in BGLS was delayed compared with that of RGLS. These indicated that the absorption of RGLS was better than that of BGLS, and the sporoderm might hinder the absorption of the active components. These results increase our understanding of the bioavailability of BGLS and RGLS and indicate that increased bioavailability is one of the main reasons for the enhanced efficacy of RGLS.

Machine learning algorithm integrates bulk and single-cell transcriptome sequencing to reveal immune-related personalized therapy prediction features for pancreatic cancer.

Pancreatic cancer (PC) is a digestive malignancy with worse overall survival. Tumor immune environment (TIME) alters the progression and proliferation of various solid tumors. Hence, we aimed to detect the TIME-related classifier to facilitate the personalized treatment of PC. Based on the 1612 immune-related genes (IRGs), we classified patients into Immune_rich and Immune_desert subgroups via consensus clustering. Patients in distinct subtypes exhibited a difference in sensitivity to immune checkpoint blockers (ICB). Next, the immune-related signature (IRS) model was established based on 8 IRGs (SYT12, TNNT1, TRIM46, SMPD3, ANLN, AFF3, CXCL9 and RP1L1) and validated its predictive efficiency in multiple cohorts. RT-qPCR experiments demonstrated the differential expression of 8 IRGs between tumor and normal cell lines. Patients who gained lower IRS score tended to be more sensitive to chemotherapy and immunotherapy, and obtained better overall survival compared to those with higher IRS scores. Moreover, scRNA-seq analysis revealed that fibroblast and ductal cells might affect malignant tumor cells via MIF-(CD74+CD44) and SPP1-CD44 axis. Eventually, we identified eight therapeutic targets and one agent for IRS high patients. Our study screened out the specific regulation pattern of TIME in PC, and shed light on the precise treatment of PC.

Synthesis, anti-leukemia activity, and molecular docking of novel 3,16-androstenedione derivatives.

In this study, we synthesized androsta-4,14-diene-3,16-dione, 12ß-hydroxyandrosta-4,14-diene-3,16-dione, and other 3,16-androstenedione derivatives from commercially available dehydroepiandrosterone as a starting material in 9-13 steps with high yields. The bioactivity of the obtained compounds was evaluated. Compounds 14a and 23a were shown to have high antitumor activity against acute lymphoblastic leukemia cell lines Nalm-6 and BALL-1, respectively. Network pharmacology analysis showed that the anti-leukemia activity of compounds 14a and 23a might be related to the JAK2, ABL1 protein, and PI3K/Akt signaling pathways. The molecular docking of compounds 14a and 23a identified possible active sites, with the lowest docking scores for PTGS2 and MAPK14, respectively. In addition, the absorption, distribution, metabolism, and excretion prediction results revealed the drug-likeness of the two compounds. Therefore, compounds 14a and 23a should be considered anti-leukemia candidates in future studies.

Comprehensive machine learning-generated classifier identifies pro-metastatic characteristics and predicts individual treatment in pancreatic cancer: A multicenter cohort study based on super-enhancer profiling.

Rationale: Accumulating evidence illustrated that the reprogramming of the super-enhancers (SEs) landscape could promote the acquisition of metastatic features in pancreatic cancer (PC). Given the anatomy-based TNM staging is limited by the heterogeneous clinical outcomes in treatment, it is of great clinical significance to tailor individual stratification and to develop alternative therapeutic strategies for metastatic PC patients based on SEs. Methods: In our study, ChIP-Seq analysis for H3K27ac was performed in primary pancreatic tumors (PTs) and hepatic metastases (HMs). Bootstrapping and univariate Cox analysis were implemented to screen prognostic HM-acquired, SE-associated genes (HM-SE genes). Then, based on 1705 PC patients from 14 multicenter cohorts, 188 machine-learning (ML) algorithm integrations were utilized to develop a comprehensive super-enhancer-related metastatic (SEMet) classifier. Results: We established a novel SEMet classifier based on 38 prognostic HM-SE genes. Compared to other clinical traits and 33 published signatures, the SEMet classifier possessed robust and powerful performance in predicting prognosis. In addition, patients in the SEMetlow subgroup owned dismal survival rates, more frequent genomic alterations, and more activated cancer immunity cycle as well as better benefits in immunotherapy. Remarkably, there existed a tight correlation between the SEMetlow subgroup and metastatic phenotypes of PC. Among 18 SEMet genes, we demonstrated that E2F7 may promote PC metastasis through the upregulation of TGM2 and DKK1. Finally, after in silico screening of potential compounds targeted SEMet classifier, results revealed that flumethasone could enhance the sensitivity of metastatic PC to routine gemcitabine chemotherapy. Conclusion: Overall, our study provided new insights into personalized treatment approaches in the clinical management of metastatic PC patients.

Xuanfei Baidu formula alleviates impaired mitochondrial dynamics and activated NLRP3 inflammasome by repressing NF-κB and MAPK pathways in LPS-induced ALI and inflammation models.

BACKGROUND: Xuanfei Baidu Formula (XBF) is an effective traditional Chinese medicine (TCM) remedy for treating coronavirus disease 2019 (COVID-19) in China. This herbal medicine has shown effects in reducing clinical symptoms and shortening the average length of hospital stay for COVID-19 patients. Previous studies have demonstrated that XBF alleviates acute lung injury (ALI) by regulating macrophage-mediated immune inflammation, but the mechanisms of action remain elusive. PURPOSE: This study aimed to evaluate the lung-protective and anti-inflammatory effects of XBF and its underlying mechanisms. METHODS: Here, XBF's effects were investigated in an ALI mouse model induced by inhalation of atomized lipopolysaccharide (LPS). Besides, the LPS-induced inflammation model in RAW264.7 cells was used to clarify the underlying mechanisms of XBF against ALI. RESULTS: Our results showed that XBF treatment alleviated LPS-induced lung injury, as evidenced by reduced histopathological changes, pulmonary alveoli permeability, fibrosis, and apoptosis in the lung tissues. In addition, inflammation was alleviated as shown by decreased levels of tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-1ß in serum and bronchoalveolar lavage fluid (BALF), and reduced white blood cell (WBC) count in BALF. Furthermore, consistent with the in vivo assay, XBF inhibited LPS-induced inflammatory cytokines release and pro-inflammatory polarization in RAW264.7 cells. Mechanistically, XBF increased mitochondrial fusion by upregulating Mfn1 and attenuated NLRP3 inflammasome activation by repressing Casp11, respectively, to inhibit NF-κB and MAPK pathways, thus repressing pro-inflammatory macrophage polarization. CONCLUSION: In this study, we demonstrate that XBF exerts anti-ALI and -inflammatory effects by recovering mitochondrial dynamics and reducing inflammasome activation, providing a biological illustration of the clinical efficacy of XBF in treating COVID-19 patients.

The hypoxia-related signature predicts prognosis, pyroptosis and drug sensitivity of osteosarcoma.

Osteosarcoma (OS) is one of the most common types of solid sarcoma with a poor prognosis. Solid tumors are often exposed to hypoxic conditions, while hypoxia is regarded as a driving force in tumor recurrence, metastasis, progression, low chemosensitivity and poor prognosis. Pytoptosis is a gasdermin-mediated inflammatory cell death that plays an essential role in host defense against tumorigenesis. However, few studies have reported relationships among hypoxia, pyroptosis, tumor immune microenvironment, chemosensitivity, and prognosis in OS. In this study, gene and clinical data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases were merged to develop a hypoxia risk model comprising four genes (PDK1, LOX, DCN, and HMOX1). The high hypoxia risk group had a poor prognosis and immunosuppressive status. Meanwhile, the infiltration of CD8+ T cells, activated memory CD4+ T cells, and related chemokines and genes were associated with clinical survival outcomes or chemosensitivity, the possible crucial driving forces of the OS hypoxia immune microenvironment that affect the development of pyroptosis. We established a pyroptosis risk model based on 14 pyroptosis-related genes to independently predict not only the prognosis but also the chemotherapy sensitivities. By exploring the various connections between the hypoxic immune microenvironment and pyroptosis, this study indicates that hypoxia could influence tumor immune microenvironment (TIM) remodeling and promote pyroptosis leading to poor prognosis and low chemosensitivity.

An inflammatory response-related gene signature associated with immune status and prognosis of acute myeloid leukemia.

OBJECTIVE: To determine the prognostic significance of inflammatory response-associated genes in acute myeloid leukemia (AML). METHODS: Transcriptomic profiles and related clinical information of AML patients were acquired from a public database. To establish a multi-gene prognosis signature, we performed least absolute shrinkage and selection operator Cox analysis for the TCGA cohort and evaluated the ICGC cohort for verification. Subsequently, Kaplan-Meier analysis was carried out to compare the overall survival (OS) rates between high- and low-risk groups. Biological function and single-sample gene set enrichment (ssGSEA) analyses were employed to investigate the association of risk score with immune status and the tumor microenvironment. Prognostic gene expression levels in AML samples and normal controls were confirmed by qRT-PCR and immunofluorescence. RESULTS: We identified a potential inflammatory response-related signature comprising 11 differentially expressed genes, including ACVR2A, CCL22, EBI3, EDN1, FFAR2, HRH1, ICOSLG, IL-10, INHBA, ITGB3, and LAMP3, and found that AML patients with high expression levels in the high-risk group had poor OS rates. Biological function analyses revealed that prognostic genes mainly participated in inflammation and immunity signaling pathways. Analyses of cancer-infiltrating immunocytes indicated that in high-risk patients, the immune suppressive microenvironment was significantly affected. The expression of the inflammation reaction-associated signature was found to be associated with susceptibility to chemotherapy. There was a significant difference in prognostic gene expression between AML and control tissues. CONCLUSION: A novel inflammatory response-related signature was developed with 11 candidate genes to predict prognosis and immune status in AML patients.

Percutaneous local tumor ablation vs. stereotactic body radiotherapy for early-stage non-small cell lung cancer: a systematic review and meta-analysis.

BACKGROUND: Percutaneous local tumor ablation (LTA) and stereotactic body radiotherapy (SBRT) have been regarded as viable treatments for early-stage lung cancer patients. The purpose of this study was to compare the efficacy and safety of LTA with SBRT for early-stage non-small cell lung cancer (NSCLC). METHODS: PubMed, Embase, Cochrane library, Ovid, Google scholar, CNKI, and CBMdisc were searched to identify potential eligible studies comparing the efficacy and safety of LTA with SBRT for early-stage NSCLC published between January 1, 1991, and May 31, 2021. Hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were applied to estimate the effect size for overall survival (OS), progression-free survival (PFS), locoregional progression (LP), and adverse events. RESULTS: Five studies with 22,231 patients were enrolled, including 1443 patients in the LTA group and 20,788 patients in the SBRT group. The results showed that SBRT was not superior to LTA for OS (HR = 1.03, 95% CI: 0.87-1.22, P = 0.71). Similar results were observed for PFS (HR = 1.09, 95% CI: 0.71-1.67, P = 0.71) and LP (HR = 0.66, 95% CI: 0.25-1.77, P = 0.70). Subgroup analysis showed that the pooled HR for OS favored SBRT in patients with tumors sized >2 cm (HR = 1.32, 95% CI: 1.14-1.53, P = 0.0003), whereas there was no significant difference in patients with tumors sized ≤2 cm (HR = 0.93, 95% CI: 0.64-1.35, P = 0.70). Moreover, no significant differences were observed for the incidence of severe adverse events (≥grade 3) (OR = 1.95, 95% CI: 0.63-6.07, P = 0.25) between the LTA group and SBRT group. CONCLUSIONS: Compared with SBRT, LTA appears to have similar OS, PFS, and LP. However, for tumors >2 cm, SBRT is superior to LTA in OS. Prospective randomized controlled trials are required to determine such findings. INPLASY REGISTRATION NUMBER: INPLASY202160099.

Dosimetric parameters and absolute monocyte count can predict the prognosis of acute hematologic toxicity in cervical cancer patients undergoing concurrent chemotherapy and volumetric-modulated arc therapy.

PURPOSE: To explore clinical and dosimetric predictors of acute hematologic toxicity (HT) in cervical cancer patients treated with concurrent chemotherapy and volumetric-modulated arc therapy (VMAT). METHODS AND MATERIALS: We retrospectively reviewed the clinical data of 184 cervical cancer patients who had concurrent chemotherapy and VMAT. Hematological parameters were collected during the treatment period. The total pelvic bone (TPB) was delineated retrospectively for dose-volume calculations. To compare the differences between two groups, the normality test findings were used to run a paired-samples t-test or Wilcoxon signed-rank test. Pearson's correlation analysis or Spearman's correlation was used to testing the correlation between the two variables. Binary logistic regression analysis was used to analyze associations between HT and possible risk factors. The receiver operating characteristic curve(ROC) was used to evaluate the best cut-off point for dosimetric planning constraints. RESULTS: The nadir of absolute monocyte count (AMC) was found to be positively correlated with the nadir of absolute white blood cells (WBC) count (r = 0.5378, 95% CI 0.4227-0.6357, P < 0.0001) and the nadir of absolute neutrophil count(ANC) (r = 0.5000, 95% CI 0.3794-0.6039, P < 0.0001). The AMC decreased and increased before the ANC and WBC. In multivariate logistic regression analysis, the chemotherapy regimens and the TPB_V20 were independent risk factors for developing grade ≥ 3 HT. The optimal TPB_V20 cut-off value identified by ROC curves and the Youden test was 71% (AUC = 0.788; 95% CI 0.722-0.845; P value < 0.001). CONCLUSIONS: The changing trend of AMC can be used as an effective predictor for the timing and severity of the ANC/WBC nadirs and prophylactic G-CSF administration. Maintain TPB_V20 < 71% and selecting single-agent cisplatin or carboplatin could significantly reduce grade ≥ 3 HT in cervical cancer patients undergoing concurrent chemoradiotherapy.

Ferroptosis-Related IncRNAs Are Prognostic Biomarker of Overall Survival in Pancreatic Cancer Patients.

Pancreatic cancer (PC) is one of the most lethal malignancies, the mortality and morbidity of which have been increasing over the past decade. Ferroptosis, a newly identified iron-dependent cell death pattern, can be induced by iron chelators and small lipophilic antioxidants. Nonetheless, the prognostic significance of ferroptosis-related lncRNAs in PC remains to be clarified. We obtained the lncRNA expression matrix and clinicopathological information of PC patients from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) datasets in the current study. Firstly, we conducted Pearson correlation analysis to delve into the ferroptosis-related lncRNAs, and univariate Cox analysis was implemented to examine the prognostic values in PC patients. Twenty-three prognostic ferroptosis-related lncRNAs were confirmed and loaded into the least absolute shrinkage and selection operator Cox (LASSO-Cox) analysis, then a ferroptosis-related lncRNA prognostic marker (Fe-LPM) was established in the TCGA dataset. Risk scores of patients were calculated and segregated PC patients into low-risk and high-risk subgroups in each dataset. The prognostic capability of Fe-LPM was also confirmed in the ICGC dataset. Gene set enrichment analysis (GSEA) revealed that several ferroptosis-related pathways were enriched in low-risk subgroups. Furthermore, we adopted a multivariate Cox regression to establish a nomogram based on risk score, age, pathological T stage and primary therapy outcome. A competing endogenous RNA (ceRNA) network was also created relied on four of the twenty-three ferroptosis-related lncRNAs. In conclusion, the eight Fe-LPM can be utilized to anticipate the overall survival (OS) of PC patients, which are meaningful to guiding clinical strategies in PC.

Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients.

Immunotherapy has made great progress in hepatocellular carcinoma (HCC), yet there is still a lack of biomarkers for predicting response to it. Cancer stem cells (CSCs) are the primary cause of the tumorigenesis, metastasis, and multi-drug resistance of HCC. This study aimed to propose a novel CSCs-related cluster of HCC to predict patients' response to immunotherapy. Based on RNA-seq datasets from The Cancer Genome Atlas (TCGA) and Progenitor Cell Biology Consortium (PCBC), one-class logistic regression (OCLR) algorithm was applied to compute the stemness index (mRNAsi) of HCC patients. Unsupervised consensus clustering was performed to categorize HCC patients into two stemness subtypes which further proved to be a predictor of tumor immune microenvironment (TIME) status, immunogenomic expressions and sensitivity to neoadjuvant therapies. Finally, four machine learning algorithms (LASSO, RF, SVM-RFE and XGboost) were applied to distinguish different stemness subtypes. Thus, a five-hub-gene based classifier was constructed in TCGA and ICGC HCC datasets to predict patients' stemness subtype in a more convenient and applicable way, and this novel stemness-based classification system could facilitate the prognostic prediction and guide clinical strategies of immunotherapy and targeted therapy in HCC.

Interplay of four types of RNA modification writers revealed distinct tumor microenvironment and biological characteristics in pancreatic cancer.

Background: Pancreatic cancer (PC) is one of the most lethal malignancies and carries a dismal mortality and morbidity. Four types of RNA modification (namely m6A, m1A, APA and A-to-I) could be catalyzed by distinct enzymatic compounds ("writers"), mediating numerous epigenetic events in carcinogenesis and immunomodulation. We aim to investigate the interplay mechanism of these writers in immunogenomic features and molecular biological characteristics in PC. Methods: We first accessed the specific expression pattern and transcriptional variation of 26 RNA modification writers in The Cancer Genome Atlas (TCGA) dataset. Unsupervised consensus clustering was performed to divide patients into two RNA modification clusters. Then, based on the differentially expressed genes (DEGs) among two clusters, RNA modification score (WM_Score) model was established to determine RNA modification-based subtypes and was validated in International Cancer Genome Consortium (ICGC) dataset. What's more, we manifested the unique status of WM_Score in transcriptional and post-transcriptional regulation, molecular biological characteristics, targeted therapies and immunogenomic patterns. Results: We documented the tight-knit correlations between transcriptional expression and variation of RNA modification writers. We classified patients into two distinct RNA modification patterns (WM_Score_high and _low), The WM_Score_high subgroup was correlated with worse prognosis, Th2/Th17 cell polarization and oncogenic pathways (e.g. EMT, TGF-ß, and mTORC1 signaling pathways), whereas the WM_Score_low subgroup associated with favorable survival rate and Th1 cell trend. WM_Score model also proved robust predictive power in interpreting transcriptional and post-transcriptional events. Additionally, the potential targeted compounds with related pathways for the WM_Score model were further identified. Conclusions: Our research unfolds a novel horizon on the interplay network of four RNA modifications in PC. This WM_Score model demonstrated powerful predictive capacity in epigenetic, immunological and biological landscape, providing a theoretical basis for future clinical judgments of PC.

Development and Verification of the Hypoxia- and Immune-Associated Prognostic Signature for Pancreatic Ductal Adenocarcinoma.

We aim to construct a hypoxia- and immune-associated risk score model to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). By unsupervised consensus clustering algorithms, we generate two different hypoxia clusters. Then, we screened out 682 hypoxia-associated and 528 immune-associated PDAC differentially expressed genes (DEGs) of PDAC using Pearson correlation analysis based on the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression project (GTEx) dataset. Seven hypoxia and immune-associated signature genes (S100A16, PPP3CA, SEMA3C, PLAU, IL18, GDF11, and NR0B1) were identified to construct a risk score model using the Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, which stratified patients into high- and low-risk groups and were further validated in the GEO and ICGC cohort. Patients in the low-risk group showed superior overall survival (OS) to their high-risk counterparts (p < 0.05). Moreover, it was suggested by multivariate Cox regression that our constructed hypoxia-associated and immune-associated prognosis signature might be used as the independent factor for prognosis prediction (p < 0.001). By CIBERSORT and ESTIMATE algorithms, we discovered that patients in high-risk groups had lower immune score, stromal score, and immune checkpoint expression such as PD-L1, and different immunocyte infiltration states compared with those low-risk patients. The mutation spectrum also differs between high- and low-risk groups. To sum up, our hypoxia- and immune-associated prognostic signature can be used as an approach to stratify the risk of PDAC.

The Relationship Between the Change of Intraocular Lens Position and Capsular Bend After Cataract Surgery.

PURPOSE: To explore the relationship between the change in intraocular lens (IOL) position and capsular bend after cataract surgery. METHODS: Patients underwent phacoemulsification and IOL implantation (Alcon Laboratories, Inc). Patients were divided into two groups based on preoperative axial length: long axial length group (axial length ⩾ 26 mm) and normal axial length group (axial length > 22 but < 26 mm). Swept-source optical coherence tomography was performed at 1 day, 1 week, 1 month, and 3 months after mydriasis to obtain postoperative aqueous depth (PAD) and capsular bend index (CBI). The relationship between CBI and PAD changes was analyzed. RESULTS: Eighty patients (80 eyes) were included in the study. PAD decreased gradually from 1 day to 1 week and increased from 1 week to 3 months. Mean CBI was moderately positively correlated with PAD changes (r = 0.586, P < .001). The IOL moved forward gradually when the CBI was less than 2.30 and the IOL gradually moved backward when the CBI was 2.30 or greater. The root mean square of the change in PAD was smaller in the long axial length group (0.08 ± 0.04 mm) than in the normal axial length group (0.09 ± 0.05 mm) during the 3 months after surgery (P = .036). CONCLUSIONS: The position of the IOL was almost stable 1 month after operation, and postoperative capsule adhesion mainly occurred within 1 month. The change in PAD was related to capsule adhesion. The postoperative position of the IOL was relatively stable and capsular bend was relatively slow for the long axial length group over 3 months. [J Refract Surg. 2021;37(5):324-330.].

N6-Methyladenosine-Related LncRNAs Are Potential Remodeling Indicators in the Tumor Microenvironment and Prognostic Markers in Osteosarcoma.

N6-Adenosine methylation, yielding N6-methyladenosine (m6A), is a reversible epigenetic modification found in messenger RNAs and long non-coding RNAs (lncRNAs), which affects the fate of modified RNA molecules and is essential for the development and differentiation of immune cells in the tumor microenvironment (TME). Osteosarcoma (OS) is the most common primary bone tumor in children and adolescents, and is characterized by high mortality. Currently, the possible role of m6A modifications in the prognosis of OS is unclear. In the present study, we investigated the correlation between m6A-related lncRNA expression and the clinical outcomes of OS patients via a comprehensive analysis. Clinical and workflow-type data were obtained from the Genotype-Tissue Expression Program and The Cancer Genome Atlas. We examined the relationship between m6A modifications and lncRNA expression, conducted Kyoto Encyclopedia of Genes analysis and also gene set enrichment analysis (GSEA), implemented survival analysis to investigate the association of clinical survival data with the expression of m6A-related lncRNAs, and utilized Lasso regression to model the prognosis of OS. Furthermore, we performed immune correlation analysis and TME differential analysis to investigate the infiltration levels of immune cells and their relationship with clinical prognosis. LncRNA expression and m6A levels were closely associated in co-expression analysis. The expression of m6A-related lncRNAs was quite low in tumor tissues; this appeared to be a predicting factor of OS in a prognostic model, independent of other clinical features. The NOD-like receptor signaling pathway was the most significantly enriched pathway in GSEA. In tumor tissues, SPAG4 was overexpressed while ZBTB32 and DEPTOR were downregulated. Tissues in cluster 2 were highly infiltrated by plasma cells. Cluster 2 presented higher ESTIMATE scores and stromal scores, showing a lower tumor cell purity in the TME. In conclusion, m6A-related lncRNA expression is strongly associated with the occurrence and development of OS, and can be used to as a prognostic factor of OS. Moreover, m6A-related lncRNAs and infiltrating immune cells in the TME could serve as new therapeutic targets and prognostic biomarkers for OS.